Retrieval that starts with the record
Bring full-text, vectors, structured filters, and application metadata together instead of duplicating a source of truth into a separate retrieval pipeline.
KynetraDB · portable AI data plane
Your AI app needs more than a vector database.
KynetraDB brings records, retrieval, permissions, files, realtime events, and agent operations into one portable data layer—so your product can stay coherent as it learns to reason.
The product thesis
AI application data is connected. Your infrastructure should be, too.
Most teams assemble databases, vector stores, search clusters, queues, object storage, auth, and agent infrastructure into a brittle relay race. KynetraDB is designed to reduce those boundaries—without forcing you into a cloud or a black box.
Explore 100 capabilitiesFor work that compounds
A single surface for the context your model needs.
Explore
Agents with boundaries, not blind trust
Give tools a deliberate contract. Keep memory, permissions, audit events, and operational context close to the data they act on.
Portability as a product decision
Run a deployable data plane locally, in containers, on a VM, or across cloud profiles. Your app architecture need not inherit a provider’s business model.
No theatre
A product state you can inspect.
We label work by what it is: available, beta, roadmap, or research. Available catalogue entries point back to the implementation or documentation behind the claim.
- 100
- typed capabilities across retrieval, models, agents, governance, and operations
- 10
- categories so the product stays legible as the surface expands
- 4
- explicit states that separate working software from intention
Build with us
Bring your data layer
into the AI era.
Preview KynetraDB with the team building it. We’ll talk through your retrieval shape, deployment boundaries, and what should remain under your control.